Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting.

Introduction: Convolutional neural networks (CNNs) can diagnose skin cancers with impressive accuracy in experimental settings, however, their performance in the real-world clinical setting, including comparison to teledermatology services, has not been validated in prospective clinical studies.

Methods And Analysis: Participants will be recruited from dermatology clinics at the Alfred Hospital and Skin Health Institute, Melbourne. Skin lesions will be imaged using a proprietary dermoscopic camera.

From the 1990s climate change has decreased cool season catchment precipitation reducing river heights in Australia's southern Murray-Darling Basin.

The Murray-Darling Basin (MDB) is Australia's major agricultural region. The southern MDB receives most of its annual catchment runoff during the cool season (April-September). Focusing on the Murrumbidgee River measurements at Wagga Wagga and further downstream at Hay, cool season river heights are available year to year.

A suite of automated sequence analyses reduces the number of candidate deleterious variants and reveals a difference between probands and unaffected siblings.

Purpose: Develop an automated exome analysis workflow that can produce a very small number of candidate variants yet still detect different numbers of deleterious variants between probands and unaffected siblings.

Methods: Ninety-seven outbred nuclear families from the Undiagnosed Diseases Program/Network included single probands and the corresponding unaffected sibling(s). Single-nucleotide polymorphism (SNP) chip and exome analyses were performed on all, with proband and unaffected sibling considered independently as the target.

EGFR mutational genotyping of liquid based cytology samples obtained via fine needle aspiration (FNA) at endobronchial ultrasound of non-small cell lung cancer (NSCLC).

Objectives: Epidermal growth factor receptor (EGFR) gene mutation status should be determined in all patients with advanced, non-squamous non-small cell lung carcinoma (NSCLC) to guide targeted therapy with EGFR tyrosine kinase inhibitors. EGFR mutations are commonly tested by Sanger sequencing or allele specific polymerase chain reaction (ASPCR) on formalin-fixed paraffin-embedded (FFPE) samples including cell blocks (CB) that may fail due to absence of tumor cells. The cell pellet from cytology specimens obtained at the time of endobronchial guided ultrasound fine needle aspiration (EBUS FNA) (EBUS-TBNA, transbronchial needle aspiration) represents an alternative resource for additional tissue.

MYD88 L265P mutation analysis helps define nodal lymphoplasmacytic lymphoma.

The diagnosis of lymphoplasmacytic lymphoma is often challenging, especially in extramedullary tissues where the differential diagnosis includes nodal marginal zone lymphoma, splenic marginal zone lymphoma, or other small B-cell neoplasms with plasmacytic differentiation. The MYD88 L265P mutation has been recently identified in >90% of bone-marrow-based lymphoplasmacytic lymphoma, but the incidence of this abnormality and corresponding morphologic correlates in nodal lymphoplasmacytic lymphoma have not been established. We analyzed 87 cases of extramedullary lymphoplasmacytic lymphoma, splenic marginal zone lymphoma, unclassifiable splenic B-cell lymphomas, nodal marginal zone lymphoma with plasmacytic differentiation, and chronic lymphocytic leukemia/small lymphocytic lymphoma with plasmacytic differentiation for MYD88 L265P.